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An attention-based word-level interaction model: Relation detection for knowledge base question answering

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arXiv 2018年

作者： Zhang, Hongzhi Xu, Guandong Liang, Xiao Huang, Tinglei Fu, Kun CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software and Advanced Analytics University of Technology Sydney Australia

Relation detection plays a crucial role in Knowledge Base Question Answering (KBQA) because of the high variance of relation expression in the question. Traditional deep learning methods follow an encoding-comparing paradigm, where the question and the candidate relation are represented as vectors to compare their semantic similarity. Max- or average- pooling operation, which compresses the sequence of words into fixed-dimensional vectors, becomes the bottleneck of information. In this paper, we propose to learn attention-based word-level interactions between questions and relations to alleviate the bottleneck issue. Similar to the traditional models, the question and relation are firstly represented as sequences of vectors. Then, instead of merging the sequence into a single vector with pooling operation, soft alignments between words from the question and the relation are learned. The aligned words are subsequently compared with the convolutional neural network (CNN) and the comparison results are merged finally. Through performing the comparison on low-level representations, the attention-based word-level interaction model (ABWIM) relieves the information loss issue caused by merging the sequence into a fixed-dimensional vector before the comparison. The experimental results of relation detection on both SimpleQuestions and WebQuestions datasets show that ABWIM achieves state-of-the-art accuracy, demonstrating its effectiveness. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge based systems

Ship flame segmentation by fusing DASPP and PE-SCAM attention

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Ship flame segmentation by fusing DASPP and PE-SCAM attentio...

Neural Networks, information and Communication Engineering (NNICE), International Conference on

作者： Xuecong Zheng Li Chen Yaojie Chen School of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei China Wuhan Institute of Marine Electric Propulsion Wuhan Hubei China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan Hubei China

To solve the problem that the flame area of small targets on ships can not be easily segmented and the flame boundary is obviously affected by other background such as smoke, this experiment improves DeepLabV3+ algorithm from the following three aspects. Firstly, Dense Atrous Spatial Pyramid Pooling (DASPP) was improved to enhance the extraction and utilization of flame boundary and small target flame features. Secondly, in order to avoid the influence of background such as smoke around the flame, the high-level flame features and shallow flame features obtained by DASPP were combined with the improved Attention Mechanism (PE-SCAM) to obtain more context information in spatial and channel dimensions, so as to enhance the processing effect of the model on the flame and its boundaries. Finally, the traditional cross loss function is optimized to reduce the influence caused by the imbalance of positive and negative samples between the flame and the background. Experimental results show that the MIou of the proposed algorithm on the ship flame data set reaches 88.43%, which can realize the accurate segmentation of small target flames and flame boundaries on the basis of ensuring high real-time performance.

关键词： Fires Artificial neural networks Feature extraction Real-time systems Marine vehicles Context modeling

Adaptive bat algorithm for toy model of protein folding

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Journal of Bionanoscience 2014年第5期8卷 360-363页

作者： Cai, Xingjuan Li, Wuzhao Kang, Qi Wang, Lei Wu, Qidi Department of Control Science and Engineering Tongji University Shanghai201804 China Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi030024 China Department of Electrical and Mechanical Engineering Jiaxing Vocational Technical College Jiaxing314036 China Shanghai Key Laboratory of Financial Information Technology Shanghai200433 China

Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behavior of bats with varying pulse rates of emission and loudness. In this paper, a new variant which is called adaptive bat algorithm is designed and applied to solve the toy model prediction problem. In this algorithm, a linearly dynamic pulse rate selection strategy is designed. To test the performance, short sequences, Fibonacci sequence and real protein sequences are selected to compare, simulation results show adaptive bat algorithm is validity. Copyright © 2014 American Scientific Publishers.

关键词： Proteins

An Evolutionary Network Architecture Search Framework with Adaptive Multimodal Fusion for Hand Gesture Recognition

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arXiv 2024年

作者： Xia, Yizhang Song, Shihao Hou, Zhanglu Xu, Junwen Zou, Juan Liu, Yuan Yang, Shengxiang Hunan Engineering Research Center of Intelligent System Optimization and Security Key Laboratory of Intelligent Computing and Information Processing Ministry of Education of China Key Laboratory of Hunan Province for Internet of Things and Information Security Xiangtan University Hunan Province Xiangtan411105 China The Centre for Computational Intelligence School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom

Hand gesture recognition (HGR) based on multimodal data has attracted considerable attention owing to its great potential in applications. Various manually designed multimodal deep networks have performed well in multimodal HGR (MHGR), but most of existing algorithms require a lot of expert experience and time-consuming manual trials. To address these issues, we propose an evolutionary network architecture search framework with the adaptive multimodel fusion (AMF-ENAS). Specifically, we design an encoding space that simultaneously considers fusion positions and ratios of the multimodal data, allowing for the automatic construction of multimodal networks with different architectures through decoding. Additionally, we consider three input streams corresponding to intra-modal surface electromyography (sEMG), intra-modal accelerometer (ACC), and inter-modal sEMG-ACC. To automatically adapt to various datasets, the ENAS framework is designed to automatically search a MHGR network with appropriate fusion positions and ratios. To the best of our knowledge, this is the first time that ENAS has been utilized in MHGR to tackle issues related to the fusion position and ratio of multimodal data. Experimental results demonstrate that AMF-ENAS achieves state-of-the-art performance on the Ninapro DB2, DB3, and DB7 datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Evolutionary algorithms

RIPPB: A Robust and Improved PBFT Protocol for Blockchain

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RIPPB: A Robust and Improved PBFT Protocol for Blockchain

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Meng Ding Heng He Rui Qiao Xiaohu Zhou School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China School of Computing Engineering and Built Environment Birmingham City University Birmingham UK

ISBN: (纸本)9781665409858

In this paper, we propose RIPPB, a robust and improved PBFT protocol for Blockchain, to improve the quality of service for blockchain applications. At RIPPB, we introduce reputation for nodes and use reputation as the voting weight for node consensus to go against Sybil attacks. And we design a novel improved logistic regression model to assign reputations to nodes based on their behavior involved in block generation. With this model, nodes performing Stake-grinding attacks and Bribery attacks, face high reputation penalties, which is unacceptable for malicious nodes to reduce the probability of launching these attacks. In addition, RIPPB adds a pre-commit phase to the PBFT algorithm to reduce the number of inter-node communications, thus improving the performance of the protocol. Cost-of-attack analysis shows the high robustness of our protocol. Experimental results show a 28% improvement in the throughput of our protocol over PBFT.

关键词： Industrial electronics Protocols Quality of service Throughput Robustness Blockchains Behavioral sciences

Research and application of artificial intelligence based webshell detection model: A literature review

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arXiv 2024年

作者： Ma, Mingrui Han, Lansheng Zhou, Chunjie Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China

Webshell, as the"culprit" behind numerous network attacks, is one of the research hotspots in the field of cybersecurity. However, the complexity, stealthiness, and confusing nature of webshells pose significant challenges to the corresponding detection schemes. With the rise of Artificial Intelligence (AI) technology, researchers have started to apply different intelligent algorithms and neural network architectures to the task of webshell detection. However, the related research still lacks a systematic and standardized methodological process, which is confusing and redundant. Therefore, following the development timeline, we carefully summarize the progress of relevant research in this field, dividing it into three stages: Start Stage, Initial Development Stage, and In-depth Development Stage. We further elaborate on the main characteristics and core algorithms of each stage. In addition, we analyze the pain points and challenges that still exist in this field and predict the future development trend of this field from our point of view. To the best of our knowledge, this is the first review that details the research related to AI-based webshell detection. It is also hoped that this paper can provide detailed technical information for more researchers interested in AI-based webshell detection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

A generalization theory based on independent and task-identically distributed assumption

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arXiv 2019年

作者： Zheng, Guanhua Sang, Jitao Li, Houqiang Yu, Jian Xu, Changsheng University of Science and Technology of China School of Computer and Information Technology Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Chinese Academy of Sciences Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Hefei230026 China National Lab of Pattern Recognition Institute of Automation CAS Beijing100190 China University of Chinese Academy of Sciences

—Existing generalization theories analyze the generalization performance mainly based on the model complexity and training process. The ignorance of the task properties, which results from the widely used IID assumption, makes these theories fail to interpret many generalization phenomena or guide practical learning tasks. In this paper, we propose a new Independent and Task-Identically Distributed (ITID) assumption, to consider the task properties into the data generating process. The derived generalization bound based on the ITID assumption identifies the significance of hypothesis invariance in guaranteeing generalization performance. Based on the new bound, we introduce a practical invariance enhancement algorithm from the perspective of modifying data distributions. Finally, we verify the algorithm and theorems in the context of image classification task on both toy and real-world datasets. The experimental results demonstrate the reasonableness of the ITID assumption and the effectiveness of new generalization theory in improving practical generalization performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Classification (of information)

information Retrieval Technology 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Sung Hyon Myaeng Ming Zhou Kam-Fai Wong Hong-Jiang Zhang

ISBN: (数字)9783540318712

ISBN: (纸本)9783540250654

TheAsiainformationRetrievalSymposium(AIRS)wasestablishedbytheAsian information retrieval community after the successful series of information - trieval with Asian Languages (IRAL) workshops held in six di?erent locations in Asia, starting from 1996. While the IRAL workshops had their focus on inf- mation retrieval problems involving Asian languages, AIRS covers a wider scope of applications, systems, technologies and theory aspects of information retrieval in text, audio, image, video and multimedia data. This extension of the scope re?ects and fosters increasing research activities in information retrieval in this region and the growing need for collaborations across subdisciplines. We are very pleased to report that we saw a sharp increase in the number of submissions and their quality, compared to the IRAL workshops. We received 106papersfromninecountriesinAsiaandNorthAmerica,fromwhich28papers (26%) were presented in oral sessions and 38 papers in poster sessions (36%). It was a great challenge for the Program Committee to select the best among the excellent papers. The low acceptance rates witness the success of this year’s conference. After a long discussion between the AIRS 2004 Steering Committee and Springer, the publisher agreed to publish our proceedings in the Lecture Notes in Computer Science (LNCS) series, which is SCI-indexed. We feel that this strongly attests to the excellent quality of the papers.

关键词： information Storage and Retrieval information systems Applications (incl. Internet) Algorithm Analysis and Problem Complexity Data Structures Data Storage Representation Discrete Mathematics in Computer Science

A candidate solutions generator based on mixed strategy for non-rigid object extraction

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A candidate solutions generator based on mixed strategy for ...

International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Min Jiang Xiaozhou Zhou Shijie Yao Zhaohui Gan Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan University of Science and Technology Wuhan P. R. China College of Information Science and Engineering Wuhan University of Science and Technology Wuhan P. R. China

Extracting non-rigid object from images can be used in object recognition, medical image analysis, video monitoring, etc. In order to improve the efficiency and accuracy of visual object extraction, we design a candidate shape generator based on a mixture strategy, called mixture generator, it combines the image data driven method with model parameter driven method, and tends to generate valid shape in area which has a high shape prior density value by exploiting the GPDM model, so the efficiency of search is greatly improved. To prove the accuracy of our mixture generator, we have done experiments under the framework of global optimization algorithm (simulated annealing) on the FGNET face database. Experiments show that, compared with traditional ASM algorithm, our method is not only insensitive to initialization conditions, but also can put up with clutters and realize a more robust object extraction.

关键词： Shape Generators Face Active shape model Data models Simulated annealing